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Benefits of Blending Mandate in Sustainable Economies

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New Metropolitan Perspectives (NMP 2020)

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Abstract

In Europe biofuels are subject to two major regulations that fix targets for a blending share within 2020 and 2030. Blending mandates are a crucial tool for decreasing greenhouse gas emissions and for stimulating investments in ethanol plants. The investment value in ethanol plant can be viewed as a real option, more precisely as a straddle option. Real options are investment analysis tools that capture the value of managerial flexibility of strategic decisions in dynamic environments. A real option model for evaluating an investment in ethanol plant is discussed here. According to the model, higher ethanol blending shares correspond to higher investment values of the production plant. This confirms the assumption that policy measures like blending mandates help cities to be more sustainable from a pollution reduction perspective, and they stimulate investments in biofuels due to higher profits.

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Notes

  1. 1.

    Including international aviation and international shipping.

  2. 2.

    In recent years, there has been an increased interest in the study and application of real options theory regarding investment decisions in the energy sector. Projects concerning investments in the construction of renewable plants have distinctive features, and therefore require the use of tools that provide their value in a more precise way. Traditional techniques, like Net Present Value, have many limitations, and for this reason, it is preferable to use more accurate tools, such as real options. Although the use of such tools is still limited, recently some studies implementing the real options theory appeared in the literature [10,11,12].

  3. 3.

    Biofuels with 85% of ethanol (E85) are commonly used in United States for FFVs, while a 100% share (E100) has been introduced in Brazil for neat gasoline vehicles and most recently for E100 FFVs. This underlines that ethanol can be an important alternative to gasoline as a fuel.

  4. 4.

    The mandatory 10% target is the share of final energy consumed in transport, to be obtained from renewable sources in general and not only from biofuels.

  5. 5.

    Gasoline prices and ethanol prices are stochastic and evolve over time according to a mean-reverting process [23].

  6. 6.

    A straddle option is a trading strategy that consists in a combination of position in both call and put with the same strike price. This strategy is optimal when the investor is expecting large changes in a stock price but does not know in which direction they will be [24].

  7. 7.

    In the absence of blending mandates, biofuels and fossil fuels are exclusively substitutes.

  8. 8.

    Mainly due to an improved conversion efficiency of an ethanol unit and a decreasing trend in ethanol production costs.

  9. 9.

    The explicit form and the derivation of the profit function is omitted in this paper. See [21] for details.

  10. 10.

    The HJB equation is an arbitrage condition that divides the entire evaluation problem in two parts at each time point: the immediate state (represented by immediate cash flow) and the future possible state (capital gain). The stochastic dynamic programming is solved by using Ito’s lemma and partial differential equation. The detailed explanation of all theorem and mathematical steps are omitted, as they are beyond the aim of this study. See [27] for details.

  11. 11.

    The volatility parameter is inside the mathematical real option model. More precisely it is inside both option value and lower bound discount value of \( V^{1} \left( {P_{G} , P_{E} } \right) \) and \( V^{2} \left( {P_{G} , P_{E} } \right) \) respectively [21].

  12. 12.

    Solutions are generated by performing Monte Carlo simulations for a given set of US parameters.

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Correspondence to Cinzia Bonaldo .

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Bonaldo, C. (2021). Benefits of Blending Mandate in Sustainable Economies. In: Bevilacqua, C., Calabrò, F., Della Spina, L. (eds) New Metropolitan Perspectives. NMP 2020. Smart Innovation, Systems and Technologies, vol 178. Springer, Cham. https://doi.org/10.1007/978-3-030-48279-4_50

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